Example Using Multiple Effects and Multiple Levels

This example uses a proportional hazards model for the sample data, VA Lung Cancer.jmp. The data were collected from a randomized clinical trial, where males with inoperable lung cancer were placed on either a standard or a novel (test) chemotherapy (Treatment). The primary interest of this trial was to assess if the treatment type has an effect on survival time, with special interest given to the type of tumor (Cell Type). See Prentice (1973) and Kalbfleisch and Prentice (2002) for additional details about this data set.

For the proportional hazards model, covariates include the following:

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Whether the patient had undergone previous therapy (Prior)

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Age of the patient (Age)

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Time from lung cancer diagnosis to beginning the study (Diag Time)

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A general medical status measure (KPS)

Age, Diag Time, and KPS are continuous measures and Cell Type, Treatment, and Prior are categorical (nominal) variables. The four nominal levels of Cell Type include Adeno, Large, Small, and Squamous.

This example illustrates the results for a model with more than one effect and a nominal effect with more than two levels. Risk ratios are also demonstrated, with example calculations for risk ratios for a continuous effect and risk ratios for an effect that has more than two levels.

Select Help > Sample Data Library and open VA Lung Cancer.jmp.

Select Analyze > Reliability and Survival > Fit Proportional Hazards.

Select Time as Time to Event.

Select censor as Censor.

Select Cell Type, Treatment, Prior, Age, Diag Time, and KPS and click Add.

Click Run.

From the red triangle menu, select Risk Ratios.

(Optional) Click the disclosure icon on the Baseline Survival at mean title bar to close the plot, and click the disclosure icon on Whole Model to close the report.

Report Window for Proportional Hazards Model with Multiple Effects and Levels

Note the following about the results:

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In the Whole Model report, the low Prob>Chisq value (<.0001) indicates that there is a difference in survival time when at least one of the effects is included in the model.

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In the Effect Likelihood Ratio Tests report, the Prob>ChiSq values indicate that KPS and at least one of the levels of Cell Type are significant, while Treatment, Prior, Age, and Diag Time effects are not significant.